JSM 2004 - Toronto

Abstract #300982

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Activity Number: 20
Type: Contributed
Date/Time: Sunday, August 8, 2004 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics and the Environment
Abstract - #300982
Title: Bayesian Inferences on Environmental Exceedances and Their Spatial Locations
Author(s): Peter F. Craigmile*+ and Noel Cressie and Thomas J. Santner and Youlan Rao
Companies: Ohio State University and Ohio State University and Ohio State University and Ohio State University
Address: 404 Cockins Hall, Columbus, OH, 43210,
Keywords: Bayesian hierarchical models ; geostatistics ; integrated weighted quantile squared error loss ; loss functions ; Bayes predictor ; spatial statistics
Abstract:

A frequent problem in environmental science is the prediction of extrema and exceedances. It is well known that Bayesian and empirical-Bayesian predictors based on integrated squared error loss tend to "overshrink'' predictions of extrema toward the mean. We propose a new loss function called the integrated weighted quantile squared error loss (IWQSEL) as the basis for prediction of exceedances and their spatial location. The loss function is based on an ordering of the underlying spatial process using a spatially averaged cumulative distribution function. We illustrate this methodology with a Bayesian analysis of surface-nitrogen concentrations in the Chesapeake Bay.

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